Abstract
In areas where high-quality agricultural products are grown that are also highly susceptible to hailfall damage, short-term forecasting is a prerequisite, in order to evaluate the risk of hail falling. In cases such as this, where a relationship exists between a response variable and one or more explanatory variables, and the outcome variable is also binary (risk/no risk) the multiple Logistic Regression Model is a good tool to use. A collection of 15 independent meteorological variables was obtained from a sample of 229 days. The determination of risk/no risk situations was based on the meteorological information supplied by a dense network of over 500 observation points, distributed across an area of more than 6,500 km 2.
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